Defined by Gartner in 2001, big data is “high-volume, high-velocity and/or high-variety information assets that demand cost-effective, innovative forms of information processing that enable enhanced insight, decision making, and process automation.”
Big data. It’s a buzzword that sparks many conversations, especially in manufacturing. But, despite the buzz worthiness, it can provide great benefits to manufacturers where big data can take a company from predictive decision making to prescriptive decision making if done right.
It’s a lot to take in, right? When understood what those benefits are, and potential downfalls, big data can be extremely useful, especially when paired with big manufacturing analytics.
Big data is applicable in every industry – healthcare, financial, retail, and beyond. What we’re most interested in at Mingo is big data in manufacturing. It’s the big picture of what is happening with data in that industry.
When used correctly, big data can provide valuable insights.
What is Big Data in Manufacturing?
Wikipedia further explains big data as the “extremely large data sets that may be analyzed computationally to reveal patterns, trends, and associations, especially relating to human behavior and interactions.”
It should go without saying that, yes, big data is of great importance to manufacturers, but it’s possible to get lost in the sheer amount of data gathered. It brings about an interesting dilemma – too little data and you have no insight into your processes, but too much data and it becomes overly complex and overwhelming. Which begs the question, how do manufacturers create the delicate balance between the two and benefit from the use of big data?
Note: Keep in mind, the goal for smart manufacturing is to integrate all software together. Many times, this goal falls short. Read about the broken promise of smart manufacturing.
Manufacturers use a variety of manufacturing software within their company, but there is often not an easy way to tie the solutions together to get a big picture of how a factory floor is running. Industry 4.0 aims to solve this.
Think about the different types of manufacturing software – ERP, MES, CMMS, manufacturing analytics – there are many options for manufacturers. When these systems are integrated via big data in manufacturing, patterns can be found, and problems can be solved, efficiently and without complexity.
John Broadbent, Founder or Realise Potential, speaks about this in detail on an episode of Zen and the Art of Manufacturing Analytics. Listen wherever you get your podcasts.
What are the Types of Big Data Used in Manufacturing?
The idea behind big data is that it creates a bigger picture of all the data collected, allowing you insight into many machines, lines, processes, and systems. Production, sensors on machines, quality, maintenance, and design data can be combined to observe patterns and pull information out of that to make thoughtful and data-driven decisions.
Big data in manufacturing can include productivity data on the amount of product you’re making to all the different measurements you must collect for a quality check. It can include how much power consumption a machine has, or the amount of water, or the air required for the machine to run. Big data is truly any piece of data that can be collected from anywhere in the company.
Big data is everywhere.
Where Do Manufacturers Generate Big Data?
Big data in manufacturing is generated from other software machines such as assets like sensors, pumps, motors, compressors, or conveyers. It’s even produced from outside partners, vendors, or customers. The most important thing to remember is that big data is everywhere. If data is produced, it can feed into the larger concept of big data.
But, remember, if you want to see benefit from a large amount of data, it’s important to follow the idea of a hub and spoke methodology. Create one “hub”, or centralized view, and feed all of the data from the “spokes” into this one single view or source of truth.
How Can Manufacturers Benefit from Data Analytics?
It goes without saying, big data in manufacturing generates a lot of data. Without analysis, the data doesn’t mean anything. In order to benefit from the data collected, data visualization, data science, or data analysis needs to be leveraged and insights need to be gained. The process of analyzing information is valuable, not only for decision making but for your company’s bottom line.
With data analytics, your company can:
- Improve manufacturing
- Customize product design
- Ensure better quality assurance
- Manage the supply chain
- Evaluate for any potential risk
Who is Using Big Data Analytics in Manufacturing Now?
Oil and gas, refineries, chemical producers, automotive, plastics, metal forming, food and beverage manufacturers are all examples of manufacturers using big data analytics. The list goes on and on and even expands beyond manufacturing. Anyone and everyone can use analytics to make data-driven decisions. Those that are seeing the most benefit, use big data efficiently by connecting all of their systems to get a big picture insight into plant performance.
It should go without saying that all Mingo customers are also using big data analytics with sensors, dashboards, and scoreboards. But as the industry continues to grow, even with the midsize companies, big data analytics is starting to get utilized more and more.
Think of big data analytics as what ties everything together. If you’re only looking at the big picture, you won’t discover any big insights, but with analytics, you can determine how and why your processes are functioning as they are. Analytics is necessary to determine how companies, and your company specifically, are growing.
The benefits of big data in manufacturing and analytics can make a monumental difference in company growth, if used right.